Crop plant phenotype analysis method and device

Abstract

The embodiment of the invention provides a crop plant phenotype analysis method and device, and belongs to the technical field of agricultural informatization. The method comprises the following steps of acquiring the plant morphological data of crop plants; inputting the plant morphological data into a crop plant morphological model, and outputting the stalk morphological data and the missing leaf morphological data of the crop plant. Due to the fact that the stem morphological data and the missing leaf morphological data of the crop plants can be directly obtained through the crop plant morphological model on the scale of the single plant, compared with a three-dimensional reconstruction mode, the workload is smaller, the efficiency is higher, and the high-throughput phenotypic analysis can be conveniently achieved. In addition, only the external leaves of the wheat plant three-dimensional model constructed by the three-dimensional reconstruction methods, such as multi-view imaging. three-dimensional laser radar, etc., has the relatively higher resolution ratio, the point cloud noise of stalks and leaves close to the center of a plant is high, and the accurate three-dimensional reconstruction is difficult to achieve, but the accurate three-dimensional reconstruction and phenotypic analysis can be achieved through the embodiment of the invention.

Description

technical field [0001] The invention relates to the technical field of agricultural informatization, in particular to a crop plant phenotype analysis method and device. Background technique [0002] Rice and wheat are important food crops. Rapid and high-throughput acquisition of three-dimensional phenotypic information of rice and wheat plants is of great importance for genotype-phenotype association analysis research, new variety selection and high-yield cultivation of rice and wheat. significance. However, the complex morphological structure of rice and wheat, with many tillers and thin leaves and stems, brings great challenges to the acquisition of 3D data and phenotypic information. In related technologies, the acquisition of rice and wheat phenotype information is mostly concentrated at the population scale. By mounting lidar, visible light, and multispectral sensors on drones, orbital phenotyping platforms, and vehicle-mounted phenotyping platforms, etc., rice phenot...

AI Technical Summary

Problems solved by technology

[0003] At the individual plant scale, although the three-dimensional digital data of rice and wheat plants obtained by using three-dimensional digital methods has high precision and good three-dimensional reconstruction results, the efficiency is too low and the workload is heavy, making it difficult to achieve high-throughput analysis of rice and wheat plant phenotypes

In addition, due to the thin stems of rice and wheat leaves and the large occlusion of the center of the plants, the 3D data of rice and wheat plants acquired by means of multi-view imaging, 3D laser scanning, and time-of-flight cameras are seriously missing, making it difficult to achieve accurate 3D plant data. Data Acquisition and High-Throughput Phenotype Interpretation

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